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ObjectiveA quality control (QC) system based on the electronic portal imaging device (EPID) system was used to realize the Multi-Leaf Collimator (MLC) position verification and dose verification functions on Primus and VenusX accelerators. Methods The MLC positions were calculated by the maximum gradient method of gray values to evaluate the deviation. The dose of images acquired by EPID were reconstructed using the algorithm combining dose calibration and dose calculation. The dose data obtained by EPID and two-dimensional matrix (MapCheck/PTW) were compared with the dose calculated by Pinnacle/TiGRT TPS for \begin{document}$ \gamma $\end{document} passing rate analysis. ResultsThe position error of VenusX MLC was less than 1 mm. The position error of Primus MLC was significantly reduced after being recalibrated under the instructions of EPID. For the dose reconstructed by EPID, the average \begin{document}$ \gamma $\end{document} passing rates of Primus were 98.86% and 91.39% under the criteria of 3%/3 mm, 10% threshold and 2%/2 mm, 10% threshold, respectively. The average \begin{document}$ \gamma $\end{document} passing rates of VenusX were 98.49% and 91.11%, respectively.ConclusionThe EPID-based accelerator quality control system can improve the efficiency of accelerator quality control and reduce the workload of physicists.

Objective To observe the effects of Yishen Huoxue Tongqiao method on the PI3K/AKT signaling pathway and oxidative stress expression level in the medial vestibular nucleus of aging model rats induced by intraperitoneal injection of D-galactose, and to explore the mechanism of Yishen Huoxue Tongqiao method in delaying the aging of the medial vestibular nucleus. Methods After adaptive feeding of 18 rats for 7 days, they were randomly divided into a blank group, a model group, and a Traditional Chinese Medicine group, with 6 rats in each group.The blank group was intraperitoneally injected with 500 mg/(kg·d) of physiological saline, while the model group and Traditional Chinese Medicine group were intraperitoneally injected with 500 mg/(kg·d) of D-galactose for 8 consecutive weeks.After successful modeling, the blank group and model group were orally administered physiological saline at 18.45 g/(kg·d), while the Traditional Chinese Medicine group was orally administered Yishen Huoxue Tongqiao decoction at 18.45 g/(kg·d) for 8 consecutive weeks.The vestibular function of each group of rats 2 hours after the last administration was evaluated, and the samples from the medial vestibular nucleus were collected.The expression levels of glutathione(GSH), malondialdehyde(MDA), reactive oxygen species(ROS) in each group were detected by the Elisa method, and the expression levels of PI3K and AKT1 in the medial vestibular nucleus were detected by the Western blot method. Results There was no statistically significant difference in the success rates of three sets of aerial righting reflex tests(P>0.05).The head deviation angle of the model group and the Traditional Chinese Medicine group was greater than that of the blank group, while the head deviation angle of the Traditional Chinese Medicine group was smaller than that of the model group, and the differences were statistically significant(P

In this work, Cu/1060Al bimetallic composite materials manufactured by high-temperature free-oxygen rolling process are reported. The results show that with the increase of rolling passes, the microstructure of Cu and 1060Al gradually extends and elongates in the rolling direction, and the interface that has few compounds is dominated by mechanical bonding. It is worth noting that layered fracture occurs during the tensile process. After annealing, the interface changes from mechanical bonding to metallurgical bonding, and the layered fracture is alleviated under the traction of the interface layer. With the increase of annealing time and temperature, the thickness of the interface compounds gradually increase, and the interface compounds from the copper layer to the aluminum layer are Cu9Al4, CuAl and CuAl2, respectively. Annealing at 350 °C for 2 h exhibits the best comprehensive performance, a tensile strength of 138 MPa and an elongation of 64 %. Tensile behavior in the rolled state and annealed state has been discussed based on failure theory, and compound growth after annealing has been analyzed on account of the theories of dynamics and thermodynamics.

Abstract Objective This study aimed to present a deep-learning network called contrastive learning-based cycle generative adversarial networks (CLCGAN) to mitigate streak artifacts and correct the CT value in four-dimensional cone beam computed tomography (4D-CBCT) for dose calculation in lung cancer patients. Methods 4D-CBCT and 4D computed tomography (CT) of 20 patients with locally advanced non-small cell lung cancer were used to paired train the deep-learning model. The lung tumors were located in the right upper lobe, right lower lobe, left upper lobe, and left lower lobe, or in the mediastinum. Additionally, five patients to create 4D synthetic computed tomography (sCT) for test. Using the 4D-CT as the ground truth, the quality of the 4D-sCT images was evaluated by quantitative and qualitative assessment methods. The correction of CT values was evaluated holistically and locally. To further validate the accuracy of the dose calculations, we compared the dose distributions and calculations of 4D-CBCT and 4D-sCT with those of 4D-CT. Results The structural similarity index measure (SSIM) and peak signal-to-noise ratio (PSNR) of the 4D-sCT increased from 87% and 22.31 dB to 98% and 29.15 dB, respectively. Compared with cycle consistent generative adversarial networks, CLCGAN enhanced SSIM and PSNR by 1.1% (p

Abstract In the field of meteorology, the global radar network is indispensable for detecting weather phenomena and offering early warning services. Nevertheless, radar data frequently exhibit anomalies, including gaps and clutter, arising from atmospheric refraction, equipment malfunctions, and other factors, resulting in diminished data quality. Traditional radar blockage correction methods, such as employing approximate radial information interpolation and supplementing missing data, often fail to effectively exploit potential patterns in massive radar data, for the large volume of data precludes a thorough analysis and understanding of the inherent complex patterns and dependencies through simple interpolation or supplementation techniques. Fortunately, edge computing possesses certain data processing capabilities and cloud center boasts substantial computational power, which together can collaboratively offer timely computation and storage for the correction of radar beam blockage. To this end, an edge-cloud collaborative driven deep learning model named DenMerD is proposed in this paper, which includes dense connection module and merge distribution (MD) unit. Compared to existing models such as RC-FCN, DenseNet, and VGG, this model greatly improves key performance metrics, with 30.7 $$\%$$ % improvement in Critical Success Index (CSI), 30.1 $$\%$$ % improvement in Probability of Detection (POD), and 3.1 $$\%$$ % improvement in False Alarm Rate (FAR). It also performs well in the Structure Similarity Index Measure (SSIM) metrics compared to its counterparts. These findings underscore the efficacy of the design in improving feature propagation and beam blockage accuracy, and also highlights the potential and value of mobile edge computing in processing large-scale meteorological data.

Abstract Optical tomography has emerged as a non-invasive imaging method, providing three-dimensional insights into subcellular structures and thereby enabling a deeper understanding of cellular functions, interactions, and processes. Conventional optical tomography methods are constrained by a limited illumination scanning range, leading to anisotropic resolution and incomplete imaging of cellular structures. To overcome this problem, we employ a compact multi-core fibre-optic cell rotator system that facilitates precise optical manipulation of cells within a microfluidic chip, achieving full-angle projection tomography with isotropic resolution. Moreover, we demonstrate an AI-driven tomographic reconstruction workflow, which can be a paradigm shift from conventional computational methods, often demanding manual processing, to a fully autonomous process. The performance of the proposed cell rotation tomography approach is validated through the three-dimensional reconstruction of cell phantoms and HL60 human cancer cells. The versatility of this learning-based tomographic reconstruction workflow paves the way for its broad application across diverse tomographic imaging modalities, including but not limited to flow cytometry tomography and acoustic rotation tomography. Therefore, this AI-driven approach can propel advancements in cell biology, aiding in the inception of pioneering therapeutics, and augmenting early-stage cancer diagnostics.

Bioremediation is a promising strategy to remove crude oil contaminants. However, limited studies explored the potential of bacterial consortia on crude oil biodegradation in high salinity soil. In this study, four halotolerant strains (Pseudoxanthomonas sp. S1-2, Bacillus sp. S2-A, Dietzia sp. CN-3, and Acinetobacter sp. HC8-3S), with strong environmental tolerance (temperature, pH, and salinity), distinctive crude oil degradation, and beneficial biosurfactant production, were combined to construct a bacterial consortium. The inoculation of the consortium successfully degraded 97.1% of total petroleum hydrocarbons in 10 days, with notable removal of alkanes, cycloalkanes, branched alkanes, and aromatic hydrocarbons. Functional optimization showed that this consortium degraded crude oil effectively in a broad range of temperature (20–37 °C), pH (6–9), and salinity (0–100 g/L). In salt-enriched crude-oil-contaminated soil microcosms, the simultaneous treatment of bioaugmentation and biostimulation achieved the highest crude oil degradation rate of 568.6 mg/kg/d, compared to treatments involving abiotic factors, natural attenuation, biostimulation, and bioaugmentation after 60 days. Real-time PCR targeting the 16S rRNA and alkB genes showed the good adaptability and stability of this consortium. The degradation property of the constructed bacterial consortium and the engineered consortium strategy may have potential use in the bioremediation of crude oil pollution in high-salinity soil.

Abstract Background CHF (Congenital hepatic fibrosis) is a rare hereditary disease characterized by periportal fibrosis and ductal plate malformation. Little is known about the clinical presentations and outcome in CHF patients with an extraordinary complication with biliary sepsis. Case summary Our case described a 23-year-old female diagnosed as CHF combined with biliary sepsis. Her blood culture was positive for KP (Klebsiella pneumoniae), and with a high level of CA19-9 (> 1200.00 U/ml, ref: G (p. V1287G) and c.9059T > C (p. L3020P) in PKHD1 gene. After biliary sepsis relieved, her liver function test was normal, and imaging examination results showed no significant difference with the results harvested during her biliary sepsis occurred. Conclusion The diagnosis of CHF complicated with biliary sepsis in the patient was made. Severely biliary sepsis due to KP infection may not inevitably aggravate congential liver abnormality in young patients. Our case provides a good reference for timely treatment of CHF patients with biliary sepsis.

Background/Objective: This study aimed to investigate the causal relationship between urate level and female infertility using Mendelian randomization (MR) analysis. Methods: To identify instrumental variables, we selected independent genetic loci associated with serum urate levels in individuals of European ancestry, utilizing data from large-scale genome-wide association studies (GWAS). The GWAS dataset included information on serum urate levels from 288,649 CKDGen participants. Female infertility data, including different etiologic classifications, consisted of 13,142 female infertility patients and 107,564 controls. We employed four MR methods, namely inverse variance weighted (IVW), MR-Egger, weighted median, and weighted model, to investigate the causal relationship between urate levels and female infertility. The Cochran Q-test was used to assess heterogeneity among single nucleotide polymorphisms (SNPs), and the MR-Egger intercept test was employed to evaluate the presence of horizontal pleiotropy. Additionally, a “leave-one-out” sensitivity analysis was conducted to examine the influence of individual SNPs on the MR study. Results: The IVW analysis demonstrated that elevated serum urate levels increased the risk of female infertility (odds ratio [OR] = 1.18, 95% confidence interval [CI]: 1.07–1.33). Furthermore, serum urate levels were found to be associated with infertility due to cervical, vaginal, or other unknown causes (OR = 1.16, 95% CI: 1.06–1.26), also confirmed by other methods. Heterogeneity among instrumental variables was assessed using Cochran’s Q-test (p < 0.05), so a random-effects IVW approach was employed in the effects model. The MR-Egger intercept test indicated no presence of horizontal pleiotropy. A “leave-one-out” sensitivity analysis was conducted, demonstrating that no individual SNP had a substantial impact on the overall findings. Conclusions: In the European population, the urate level is significantly and causally associated with an increased risk of female infertility.

The synergy effect of high K-low Ca-high Si biomass ash-based model system (BAMS) on the synthesis gas output and reaction characteristics of petroleum coke (PC) steam gasification process was studied using three biomass ash (BA) components, KCl, SiO2, and CaCO3, which were used as the model compounds. In the ternary model system, the steam gasification experiment of PC was conducted using a fixed bed reactor and gas phase chromatography. The synergistic effects of binary and ternary components in the ternary model system on the gasification of PC were obtained. These investigations were based on the data from the gas analysis and examined the gasification reaction process, syngas release behavior, and reaction characteristics. This study examined the effects of binary and ternary components in the ternary model system on the evolution of semi-char structure during PC gasification. This correlation revealed the synergistic effect of the model system on PC gasification. Scanning electron microscope (SEM) and Raman spectroscopy were used to characterize the structure and surface microstructure of the gasification semi-char. The results showed that the yields of different gases in the ternary model system were in H2 > CO > CO2. Compared with single PC gasification, the yields of H2, CO, syngas, and carbon conversion were increased by 29.42 mmol/g, 20.40 mmol/g, 56.68 mmol/g, and 0.35, respectively. All other components in the ternary model system with high K-low Ca-high Si demonstrated catalytic effect, except for SiO2 and the Ca-Si system, which showed inhibitory effects on syngas release and reaction features. Integrating SEM and Raman spectroscopic analyses, it was elucidated that CaCO3 and KCl diminished the degree of graphitization in semi-char through interactions with the carbonaceous matrix. This phenomenon facilitated the gasification process and exhibited a synergistic effect. Secondly, SiO2 will react with CaCO3 and KCl, producing inert silicates and inactivating these compounds, leading to the decline of catalysis.

Abstract Background and Objectives Surgery is an essential treatment for non‐distant metastatic cutaneous melanoma (NMCM). We aim to construct and validate prognostic nomograms based on surgical approaches and the clinicopathological characteristics of NMCM patients. Methods Data of patients diagnosed with cutaneous melanoma from 2004 to 2015 were identified from the Surveillance, Epidemiology, and End Results (SEER) database. Two online nomograms were constructed to predict the 3, 5‐year melanoma‐specific survival (MSS) for NMCM patients based on the surgical approaches. These nomograms were evaluated by the dynamic Harrell's concordance index (C‐index), decision curve analysis and clinical impact curve. Both internal and external data verification were conducted. Results A total of 14,091 NMCM cases were included in this study. The C‐index of the nomograms for the excisional surgery group and amputation group were 0.818 and 0.806, respectively, and 0.763 and 0.731, respectively, in our hospital data validation. After internal and bootstrap verification, our two nomograms showed good accuracy and practicality. Conclusion NMCM patients exhibited equal survival rates independent of resection margin size, while those who needed amputation had worse survival rates. We generated two online nomograms distinguished by surgical approach to predict NMCM patient survival based on clinicopathological characteristics.

Abstract The outer membrane (OM) of Gram-negative bacteria such as Escherichia coli is an asymmetric bilayer with the glycolipid lipopolysaccharide (LPS) in the outer leaflet and glycerophospholipids in the inner. Nearly all integral OM proteins (OMPs) have a characteristic β-barrel fold and are assembled in the OM by the BAM complex, which contains one essential β-barrel protein (BamA), one essential lipoprotein (BamD), and three non-essential lipoproteins (BamBCE). A gain-of-function mutation in bamA enables survival in the absence of BamD, showing that the essential function of this protein is regulatory. Here, we demonstrate that the global reduction in OMPs caused by BamD loss weakens the OM, altering cell shape and causing OM rupture in spent medium. To fill the void created by OMP loss, phospholipids (PLs) flip into the outer leaflet. Under these conditions, mechanisms that remove PLs from the outer leaflet create tension between the OM leaflets, which contributes to membrane rupture. Rupture is prevented by suppressor mutations that release the tension by halting PL removal from the outer leaflet. However, these suppressors do not restore OM stiffness or normal cell shape, revealing a possible connection between OM stiffness and cell shape.

Rationale and objectivesTo construct a predictive model for benign and malignant peripheral pulmonary lesions (PPLs) using a random forest algorithm based on grayscale ultrasound and ultrasound contrast, and to evaluate its diagnostic value.Materials and methodsWe selected 254 patients with PPLs detected using chest lung computed tomography between October 2021 and July 2023, including 161 malignant and 93 benign lesions. Relevant variables for judging benign and malignant PPLs were screened using logistic regression analysis. A model was constructed using the random forest algorithm, and the test set was verified. Correlations between these relevant variables and the diagnosis of benign and malignant PPLs were evaluated.ResultsAge, lesion shape, size, angle between the lesion border and chest wall, boundary clarity, edge regularity, air bronchogram, vascular signs, enhancement patterns, enhancement intensity, homogeneity of enhancement, number of non-enhancing regions, non-enhancing region type, arrival time (AT) of the lesion, lesion-lung AT difference, AT difference ratio, and time to peak were the relevant variables for judging benign and malignant PPLs. Consequently, a model and receiver operating characteristic curve were constructed with an AUC of 0.92 and an accuracy of 88.2%. The test set results showed that the model had good predictive ability. The index with the highest correlation for judging benign and malignant PPLs was the AT difference ratio. Other important factors were lesion size, patient age, and lesion morphology.ConclusionThe random forest algorithm model constructed based on clinical data and ultrasound imaging features has clinical application value for predicting benign and malignant PPLs.

The development and application of lightweight materials boasting an elevated elastic modulus have emerged as a focal point in the realm of materials research. A novel Mg-8Li-3Al-2Zn-0.5Y (wt.%, LAZ832) matrix composite reinforced with ex situ micron-sized TiB2 particles was introduced in this work. The uniformly distributed TiB2 particles were achieved through ball milling pretreatment and subsequent hot extrusion. A comprehensive analysis of the composite's microstructure and mechanical properties was conducted. Mg-Li-Al-Zn precipitation regions formed at the TiB2 interface was identified firstly. This softening region significantly enhanced the ductility of the composite by reducing the dislocation density and stress concentration around the TiB2 particles. The ductility and the elastic modulus of the as-extruded composite increased significantly with ideal ultimate tensile strength (UTS = 270 MPa). This work highlights an ultra-light Mg-Li matrix composite attaining high modulus (60 GPa) and notable elongation to fracture (19.1 %), demonstrating significant potential for future applications.

Characterized by severe deficits in communication, most individuals with autism spectrum conditions (ASC) experience significant language dysfunctions, thereby impacting their overall quality of life. Wernicke's area, a classical and traditional brain region associated with language processing, plays a substantial role in the manifestation of language impairments. The current study carried out a mega-analysis to attain a comprehensive understanding of the neural mechanisms underpinning ASC, particularly in the context of language processing. The study employed the Autism Brain Image Data Exchange (ABIDE) dataset, which encompasses data from 443 typically developing (TD) individuals and 362 individuals with ASC. The objective was to detect abnormal functional connectivity (FC) between Wernicke's area and other language-related functional regions, and identify frequency-specific altered FC using Wernicke's area as the seed region in ASC. The findings revealed that increased FC in individuals with ASC has frequency-specific characteristics. Further, in the conventional frequency band (0.01–0.08 Hz), individuals with ASC exhibited increased FC between Wernicke's area and the right thalamus compared with TD individuals. In the slow-5 frequency band (0.01–0.027 Hz), increased FC values were observed in the left cerebellum Crus II and the right lenticular nucleus, pallidum. These results provide novel insights into the potential neural mechanisms underlying communication deficits in ASC from the perspective of language impairments.

Tuina is a treatment method in traditional Chinese medicine which has analgesic effects and effectively alleviates the symptoms of neuropathic pain (NP). Transient receptor potential vanilloid type 1 (TRPV1) and transient receptor potential ankyrin type 1 (TRPA1) play major roles in transmitting nociceptive sensory signals in the nociceptive primary sensory dorsal root ganglion (DRG) nerve. The nitric oxide (NO)/cyclic guanosine 3′,5′-monophosphate(cGMP) pathway exerts both nociceptive and antinociceptive effects in various chronic pain models. TRPV1 and TRPA1 mediate the influx of calcium, which stimulates the generation of NO. Subsequently, NO activates the NO/cGMP/protein kinase G (PKG) signaling pathway, thereby improving hyperalgesia. In the present study, oa rat model of NP with minor chronic constriction injury (CCI) of the right sciatic nerve of NP was established. The results of behavioral testing showed that, after a one-time tuina intervention, the mechanical withdrawal threshold (MWT) and thermal withdrawal latency (TWL) were prolonged to varying degrees in the tuina group compared with the model group. Similarly, the expression of TRPV1, TRPA1, NO, soluble guanylate cyclase β (sGCβ), cGMP, and PKG1 was significantly decreased in the DRG of the tuina and tuina + TRPV1/TRPA1 antagonist group was significantly decreased. These findings suggest that the tuina intervention can effectively improve the symptoms of thermal and mechanical allodynia caused by peripheral nerve injuries. Tuina exerts immediate analgesic effects through the TRPV1/TRPA1-NO-cGMP-PKG signaling pathway.

In this paper, the 1-D compressible non-isentropic Euler equations with the source term $ \beta\rho|u|^ \alpha u $ in a bounded domain are considered. First, we study the existence of steady flows which can keep the upstream supersonic or subsonic state. Then, by wave decomposition and uniform prior estimations, we prove the global existence and stability of smooth solutions under small perturbations around the steady supersonic flow. Moreover, we get that the smooth supersonic solution is a temporal periodic solution with the same period as the boundary, after a certain start-up time, once the boundary conditions are temporal periodic.

Abstract The enhanced membrane stability and chemical versatility of polymeric vesicles have made them promising tools in micro/nanoreactors, drug delivery, cell mimicking, etc. However, shape control over polymersomes remains a challenge and has restricted their full potential. Here we show that local curvature formation on the polymeric membrane can be controlled by applying poly(N-isopropylacrylamide) as a responsive hydrophobic unit, while adding salt ions to modulate the properties of poly(N-isopropylacrylamide) and its interaction with the polymeric membrane. Polymersomes with multiple arms are fabricated, and the number of arms could be tuned by salt concentration. Furthermore, the salt ions are shown to have a thermodynamic effect on the insertion of poly(N-isopropylacrylamide) into the polymeric membrane. This controlled shape transformation can provide evidence for studying the role of salt ions in curvature formation on polymeric membranes and biomembranes. Moreover, potential stimuli-responsive non-spherical polymersomes can be good candidates for various applications, especially in nanomedicine.

Purpose – This study purposes to study the influence of artificial freezing on the liquefaction characteristics of Nanjing sand, as well as its mechanism. Design/methodology/approach – was studied through dynamic triaxial tests by means of the GDS dynamic triaxial system on Nanjing sand extensively discovered in the middle and lower reaches of the Yangtze River under seismic load and metro train vibration load, respectively, and potential hazards of the two loads to the freezing construction of Nanjing sand were also identified in the tests. Findings – The results show that under both seismic load and metro train vibration load, freeze-thaw cycles will significantly reduce the stiffness and liquefaction resistance of Nanjing sand, especially in the first freeze-thaw cycle; the more freeze-thaw cycles, the worse structural behaviors of silty-fine sand, and the easier to liquefy; freeze-thaw cycles will increase the sensitivity of Nanjing sand's dynamic pore pressure to dynamic load response; the lower the freezing temperature and the effective confining pressure, the worse the liquefaction resistance of Nanjing sand after freeze-thaw cycles; compared to the metro train vibration load, the seismic load in Nanjing is potentially less dangerous to freezing construction of Nanjing sand. Originality/value – The research results are helpful to the construction of the artificial ground freezing of the subway crossing passage in the lower reaches of the Yangtze River and to ensure the construction safety of the subway tunnel and its crossing passage.

In recent years, the field of microrobots has exploded, yielding many exciting new functions and applications, from object grasping and release to in vivo drug transport. Smart responsive materials have had a profound impact on the field of microrobots and have given them unique functions and structures. We analyze three aspects of microrobots, in which the future development of microrobots requires more efforts to be invested, and in which smart materials play a significant role in the development of microrobots. These three aspects are smart materials for building microrobots, manufacturing methods, and the functions and applications they achieve. In this review, we discuss the deformation mechanism of materials in response to external stimuli, starting from smart materials, and discuss fabrication methods to realize microrobots, laying the theoretical foundation for future smart material-based microrobots to realize their intelligence and programmability.

The corrosion behavior of 20G and TP347H materials was investigated in molten LiCl-NaCl-KCl salt. The corrosion rates of these materials in molten chloride salt are high and are strongly affected by the alloying surface oxide formation. The 20G shows uniform surface corrosion with almost no protective oxide formation on the surface. In contrast, the austenitic steel TP347H exhibits better corrosion resistance in molten chloride salts due to its high Cr content. Owing to the highly corrosive nature of molten chloride salts, the Cl− in molten salt could react with oxides and alloy, inducing intergranular corrosion of austenitic steel in molten chloride salt environments.

Immunotherapy is a clinically effective method for treating tumors. Manganese can activate the cGAS-STING signaling pathway and induce an anti-tumor immune response. However, its efficacy is hindered by non-specific distribution and low uptake rates. In this study, we employed microfluidic technology to design and develop an innovative preparation process, resulting in the creation of a novel manganese lipid nanoparticle (LNM). The lipid manganese nanoparticle produced in this process boasts a high manganese payload, excellent stability, the capacity for large-scale production, and high batch repeatability. LNM has effectively demonstrated the ability to activate the cGAS-STING signaling pathway, induce the production of pro-inflammatory cytokines, and inhibit tumor development. Notably, LNM does not require combination chemotherapy drugs or other immune activators. Therefore, LNM presents a safe, straightforward, and efficient strategy for anti-tumor immune activation, with the potential for scalable production.

Abstract Quantitative phase imaging (QPI) has emerged as method for investigating biological specimen and technical objects. However, conventional methods often suffer from shortcomings in image quality, such as the twin image artifact. A novel computational framework for QPI is presented with high quality inline holographic imaging from a single intensity image. This paradigm shift is promising for advanced QPI of cells and tissues.

Abstract Background Ordered transposon-insertion collections, in which specific transposon-insertion mutants are stored as monocultures in a genome-scale collection, represent a promising tool for genetic dissection of human gut microbiota members. However, publicly available collections are scarce and the construction methodology remains in early stages of development. Results Here, we describe the assembly of a genome-scale ordered collection of transposon-insertion mutants in the model gut anaerobe Bacteroides thetaiotaomicron VPI-5482 that we created as a resource for the research community. We used flow cytometry to sort single cells from a pooled library, located mutants within this initial progenitor collection by applying a pooling strategy with barcode sequencing, and re-arrayed specific mutants to create a condensed collection with single-insertion strains covering >2500 genes. To demonstrate the potential of the condensed collection for phenotypic screening, we analyzed growth dynamics and cell morphology. We identified both growth defects and altered cell shape in mutants disrupting sphingolipid synthesis and thiamine scavenging. Finally, we analyzed the process of assembling the B. theta condensed collection to identify inefficiencies that limited coverage. We demonstrate as part of this analysis that the process of assembling an ordered collection can be accurately modeled using barcode sequencing data. Conclusion We expect that utilization of this ordered collection will accelerate research into B. theta physiology and that lessons learned while assembling the collection will inform future efforts to assemble ordered mutant collections for an increasing number of gut microbiota members.

In this paper, the degradation behaviors of the ferroelectric gate Gallium nitride (GaN) high electron mobility transistor (HEMT) under positive gate bias stress are discussed. Devices with a gate dielectric that consists of pure Pb(Zr,Ti)O3 (PZT) and a composite PZT/Al2O3 bilayer are studied. Two different mechanisms, charge trapping and generation of traps, both contribute to the degradation. We have observed positive threshold voltage shift in both kinds of devices under positive gate bias stress. In the devices with a PZT gate oxide, we have found the degradation is owing to electron trapping in pre-existing oxide traps. However, the degradation is caused by electron trapping in pre-existing oxide traps and the generation of traps for the devices with a composite PZT/Al2O3 gate oxide. Owing to the large difference in dielectric constants between PZT and Al2O3, the strong electric field in the Al2O3 interlayer makes PZT/Al2O3 GaN HEMT easier to degrade. In addition, the ferroelectricity in PZT enhances the electric field in Al2O3 interlayer and leads to more severe degradation. According to this study, it is worth noting that the reliability problem of the ferroelectric gate GaN HEMT may be more severe than the conventional metal–insulator–semiconductor HEMT (MIS-HEMT).

In this study, the feasibility of TIG welding of as-cast Mg–8Li–3Al–2Zn-0.5Y alloys was investigated, and the quality of welded joints using different welding currents was evaluated in terms of microstructural evolution and mechanical properties. The results showed that the welding position of plates was successfully welded with good formability and no obvious welding defects at the investigated processing parameters. Significant refinement of phase size was beneficial to improve the mechanical properties of the welded joints. Under the influence of heat input, the AlLi phase in the heat-affected zone dissolved into the matrix, which improved the mechanical properties of the welded joint. The ultimate tensile strength, yield strength and elongation of the welded joint at 100 A were 224.8 MPa, 177.4 MPa and 9.9%, respectively, which is 159.5%, 159% and 43.8% of the corresponding values of the base alloy in the as-cast state. The burning loss of Li element in the welded joint was effectively controlled, which confirmed the feasibility of this welding process for welding Mg–Li alloys.

Graphical abstract for Quantitative phase imaging through an ultra-thin lensless fiber endoscope.

Membrane distillation is susceptible to thermal inefficiency and membrane wetting issues during seawater desalination. Here, authors design a MXene-engineered membrane that imparts efficient localized photothermal effect and strong water repellency, achieving sustainable freshwater production.

Abstract The generation of tailored complex light fields with multi-core fiber (MCF) lensless microendoscopes is widely used in biomedicine. However, the computer-generated holograms (CGHs) used for such applications are typically generated by iterative algorithms, which demand high computation effort, limiting advanced applications like fiber-optic cell manipulation. The random and discrete distribution of the fiber cores in an MCF induces strong spatial aliasing to the CGHs, hence, an approach that can rapidly generate tailored CGHs for MCFs is highly demanded. We demonstrate a novel deep neural network—CoreNet, providing accurate tailored CGHs generation for MCFs at a near video rate. The CoreNet is trained by unsupervised learning and speeds up the computation time by two magnitudes with high fidelity light field generation compared to the previously reported CGH algorithms for MCFs. Real-time generated tailored CGHs are on-the-fly loaded to the phase-only spatial light modulator (SLM) for near video-rate complex light fields generation through the MCF microendoscope. This paves the avenue for real-time cell rotation and several further applications that require real-time high-fidelity light delivery in biomedicine.

Objective: The aim of this study is to generate virtual noncontrast (VNC) computed tomography (CT) from intravenous enhanced CT by using Unet convolutional neural network (CNN). The differences among enhanced, VNC, and noncontrast CT in proton dose calculation were compared. Methods: A total of 30 groups of CT images of patients who received enhanced and noncontrast CT were selected. Enhanced and noncontrast CT were registered. Among these patients, 20 groups of the CT images were chosen as the training set. Enhanced CT images were used as the input, and the corresponding noncontrast CT images were used as output to train the Unet neural network. The remaining 10 groups of CT images were chosen as the test set. VNC images were generated by the trained Unet neural network. The same proton radiotherapy plan for esophagus cancer was designed based on three images. Proton dose distributions in enhanced, VNC, and noncontrast CT were calculated. The relative dose differences in enhanced CT with VNC and noncontrast CT were analyzed. Results: The mean absolute error (MAE) of the CT values between enhanced and noncontrast CT was 32.3 ± 2.6 HU. The MAE of the CT values between VNC and noncontrast CT was 6.7 ± 1.3 HU. The mean values of the enhanced CT in the great vessel, heart, lung, liver, and spinal cord were significantly higher than those of noncontrast CT, he differences were 97, 83, 42, 40, and 10 HU, respectively. The mean values of the VNC CT showed no significant difference with noncontrast CT. The differences among enhanced, VNC, and noncontrast CT in terms of the average relative proton dose for clinical target volume (CTV), heart, great vessels, and lung were also investigated. The average relative proton doses of the enhanced CT for these organs were significantly lower than those of noncontrast CT. The largest difference was observed in the great vessel, while the differences in other organs were relatively small. The γ-passing rates of the enhanced and VNC CT were calculated by 2% dose difference and 2 mm distance to agreement. Results showed that the mean γ-passing rate of VNC CT was significantly higher than enhanced CT (p

Abstract Objective To investigate the diagnostic value of serum neurofilament light chain (NFL) for discriminating Parkinson disease (PD) from Essential tremor (ET) and healthy controls, and to evaluate its correlation with some clinical features of PD patients. Methods This cross-sectional study measured NFL levels with electrochemiluminescence immunoassay in serum of 146 PD patients, 82 ET patients and 60 age-matched healthy controls. We used multivariate regression analyses to examine whether NFL contributes to PD biomarkers. Disease severity were assessed by Unified Parkinson’s Disease Rating Scale part III (UPDRS III), Hoehn & Yahr (H-Y) stage and Mini-Mental State Examination (MMSE). Results Serum NFL levels were significantly higher in PD than in ET and healthy controls (16.6 ± 3.5, 12.2 ± 2.4 and 11.8 ± 2.4 pg/mL, respectively, p

Background: Axillary lymph node (ALN) metastatic load is very important in the diagnosis and treatment of breast cancer (BC). We aimed to construct a model for predicting ALN metastatic load using deep learning radiomics (DLR) techniques based on the preoperative ultrasound and clinicopathologic information of patients with stage T 1-2 BC. Methods: Retrospective analysis was performed on 176 patients with pathologically confirmed BC in our hospital from February 2018 to April 2020. ALN metastases were divided into a low-load group (< 3 lymph node metastases) and a high-load group (≥ 3 lymph node metastases) according to pathological results. Pyradiomics and pre-trained ResNet50 were used to extract radiomics and deep learning features, respectively. Independent sample T-test, random forest recursive elimination, and Lasso were used to screen the features to construct the deep learning radiomics signature (DLRS). Based on single/multivariate logistic regression analysis results, a DLR nomogram (DLRN) model was constructed by combining valuable clinical features and DLRS. Results: The DLRS was composed of 3 radiomics features and 14 deep learning features and combined with the maximum diameter of lesions to construct the DLRN. The AUCs of the training and test sets were 0.900 (95% CI: 0.853-0.931) and 0.821 (95% CI: 0.769-0.868), respectively. The calibration curve and Hosmer–Lemeshow test confirmed that the DLRN model has a good consistency. The decision curve also confirmed its good clinical practicality. Conclusion: Ultrasound-based DLRN has an excellent performance in predicting ALN load in patients with BC.

Abstract Objective To develop high-quality synthetic CT (sCT) generation method from low-dose cone-beam CT (CBCT) images by using attention-guided generative adversarial networks (AGGAN) and apply these images to dose calculations in radiotherapy. Methods The CBCT/planning CT images of 170 patients undergoing thoracic radiotherapy were used for training and testing. The CBCT images were scanned under a fast protocol with 50% less clinical projection frames compared with standard chest M20 protocol. Training with aligned paired images was performed using conditional adversarial networks (so-called pix2pix), and training with unpaired images was carried out with cycle-consistent adversarial networks (cycleGAN) and AGGAN, through which sCT images were generated. The image quality and Hounsfield unit (HU) value of the sCT images generated by the three neural networks were compared. The treatment plan was designed on CT and copied to sCT images to calculated dose distribution. Results The image quality of sCT images by all the three methods are significantly improved compared with original CBCT images. The AGGAN achieves the best image quality in the testing patients with the smallest mean absolute error (MAE, 43.5 ± 6.69), largest structural similarity (SSIM, 93.7 ± 3.88) and peak signal-to-noise ratio (PSNR, 29.5 ± 2.36). The sCT images generated by all the three methods showed superior dose calculation accuracy with higher gamma passing rates compared with original CBCT image. The AGGAN offered the highest gamma passing rates (91.4 ± 3.26) under the strictest criteria of 1 mm/1% compared with other methods. In the phantom study, the sCT images generated by AGGAN demonstrated the best image quality and the highest dose calculation accuracy. Conclusions High-quality sCT images were generated from low-dose thoracic CBCT images by using the proposed AGGAN through unpaired CBCT and CT images. The dose distribution could be calculated accurately based on sCT images in radiotherapy.

Abstract Objectives In this study, we aimed to investigate the spontaneous neural activity in the conventional frequency band (0.01−0.08 Hz) and two sub-frequency bands (slow-4: 0.027–0.073 Hz, and slow-5: 0.01–0.027 Hz) in tension-type headache (TTH) patients with regional homogeneity (ReHo) analyses. Methods Thirty-eight TTH patients and thirty-eight healthy controls (HCs) underwent resting-state functional magnetic resonance imaging (RS-fMRI) scanning to investigate abnormal spontaneous neural activity using ReHo analysis in conventional frequency band (0.01−0.08 Hz) and two sub-frequency bands (slow-4: 0.027–0.073 Hz and slow-5: 0.01–0.027 Hz). Results In comparison with the HC group, patients with TTH exhibited ReHo increases in the right medial superior frontal gyrus in the conventional frequency band (0.01−0.08 Hz). The between group differences in the slow-5 band (0.01–0.027 Hz) highly resembled the differences in the conventional frequency band (0.01−0.08 Hz); even the voxels with increased ReHo were spatially more extensive, including the right medial superior frontal gyrus and the middle frontal gyrus. In contrast, no region showed significant between-group differences in the slow-4 band (0.027–0.073 Hz). The correlation analyses showed no correlation between the ReHo values in TTH patients and VAS scores, course of disease and number of seizures per month in conventional band (0.01−0.08 Hz), slow-4 band (0.027–0.073 Hz), as well as in slow-5 band (0.01–0.027 Hz). Conclusions The results showed that the superior frontal gyrus and middle frontal gyrus were involved in the integration and processing of pain signals. In addition, the abnormal spontaneous neural activity in TTH patients was frequency-specific. Namely, slow-5 band (0.01–0.027 Hz) might contain additional useful information in comparison to slow-4 band (0.027−0.073 Hz). This preliminary exploration might provide an objective imaging basis for the understanding of the pathophysiological mechanism of TTH.

Bacteria frequently encounter nutrient fluctuations in natural environments, yet we understand little about their ability to maintain physiological memory of previous food sources. Starvation is a particularly acute case, in which cells must balance adaptation to stresses with limited nutrient supply. Here, we show that Escherichia coli cells immediately accelerate and decelerate in growth upon transitions from spent to fresh media and vice versa, respectively, and memory of rapid growth can be maintained for many hours under constant flow of spent medium. However, after transient exposure of stationary-phase cells to fresh medium, subsequent aerobic incubation in increasingly spent medium led to lysis and limited growth when rejuvenated in fresh medium. Growth defects were avoided by incubation in anaerobic spent medium or water, suggesting that defects were caused by respiration during the process of nutrient depletion in spent medium. These findings highlight the importance of respiration for stationary phase survival and underscore the broad range of starvation outcomes depending on environmental history.

This study aims to enhance the efficiency of pickling processes by investigating the impact of strip speed and acid flow rate on the turbulence of the acid solution within the pickling tank. The research quantitatively evaluates the flow field state and distribution of acid temperature within the pickling tank. Through finite element simulation, factors such as jet velocity, strip motion velocity, and acid temperature are considered to determine the turbulence intensity, turbulent kinetic energy, convective heat transfer coefficient, and average temperature of the near-wall layer of the strip surface under the oblique jet. This analysis considers the effects of these parameters on the flow field within the pickling tank. Furthermore, simulations are conducted to assess the turbulence intensity of the acid solution under various conditions. The study reveals that the intake flow rate has a substantial influence on turbulence and temperature rise at the strip exit and inlet, albeit less so, within the acid tank itself. However, an increase in strip speed notably impacts the turbulence within the center of the acid tank. These findings are invaluable for regulating the pickling process and maintaining optimal strip surface quality in industrial production settings.

Rockburst is a complex dynamic disaster in coal mining and affected by many factors. To accurately predict the rockburst hazard among complex influencing factors, a prediction model of rockburst hazard based on the Gaussian process for binary classification (GPC) was proposed after the identification of the intrinsic relationship between multiple factors of coal mines and rockburst. Through computerized machine learning and integrated intelligent analysis, the non-linear mapping of rockburst hazard and its influencing factors was established. The multi-factor pattern recognition model was constructed using artificial intelligence. The prediction criteria of the rockburst hazard probability and the hazard probability value of the prediction area unit were determined by applying neural network and fuzzy inference methods. In addition, the rockburst hazardous zone was classified, and the corresponding technical scheme for the prevention was put forward. The validity and feasibility of the regional prediction of rockburst hazard based on GPC were verified in the engineering practice. This method is highly targeted and can improve the accuracy and precision of rockburst prediction, thus contributing to the safe and efficient production of coal mines.

Prostate cancer diagnosis is performed under ultrasound-guided puncture for pathological cell extraction. However, determining accurate prostate location remains a challenge from two aspects: (1) prostate boundary in ultrasound images is always ambiguous; (2) the delineation of radiologists always occupies multiple pixels, leading to many disturbing points around the actual contour. We proposed a boundary structure-preserving U-Net (BSP U-Net) in this paper to achieve precise prostate contour. BSP U-Net incorporates prostate shape prior to traditional U-Net. The prior shape is built by the key point selection module, which is an active shape model-based method. Then, the module plugs into the traditional U-Net structure network to achieve prostate segmentation. The experiments were conducted on two datasets: PH2 + ISBI 2016 challenge and our private prostate ultrasound dataset. The results on PH2 + ISBI 2016 challenge achieved a Dice similarity coefficient (DSC) of 95.94% and a Jaccard coefficient (JC) of 88.58%. The results of prostate contour based on our method achieved a higher pixel accuracy of 97.05%, a mean intersection over union of 93.65%, a DSC of 92.54%, and a JC of 93.16%. The experimental results show that the proposed BSP U-Net has good performance on PH2 + ISBI 2016 challenge and prostate ultrasound image segmentation and outperforms other state-of-the-art methods.

Tumor immunotherapy has shown strong therapeutic potential for stimulating or reconstructing the immune system to control and kill tumor cells. It is a promising and effective anti-cancer treatment besides surgery, radiotherapy and chemotherapy. Presently, some immunotherapy methods have been approved for clinical application, and numerous others have demonstrated promising in vitro results and have entered clinical trial stages. Although immunotherapy has exhibited encouraging results in various cancer types, however, a large proportion of patients are limited from these benefits due to specific characteristics of the tumor microenvironment such as hypoxia, tumor vascular malformation and immune escape, and current limitations of immunotherapy such as off-target toxicity, insufficient drug penetration and accumulation and immune cell dysfunction. Ultrasound-target microbubble destruction (UTMD) treatment can help reduce immunotherapy-related adverse events. Using the ultrasonic cavitation effect of microstreaming, microjets and free radicals, UTMD can cause a series of changes in vascular endothelial cells, such as enhancing endothelial cells’ permeability, increasing intracellular calcium levels, regulating gene expression, and stimulating nitric oxide synthase activities. These effects have been shown to promote drug penetration, enhance blood perfusion, increase drug delivery and induce tumor cell death. UTMD, in combination with immunotherapy, has been used to treat melanoma, non-small cell lung cancer, bladder cancer, and ovarian cancer. In this review, we summarized the effects of UTMD on tumor angiogenesis and immune microenvironment, and discussed the application and progress of UTMD in tumor immunotherapy.

Social function impairment is the core deficit of autism spectrum disorder (ASD). Although many studies have investigated ASD through a variety of neuroimaging tools, its brain mechanism of social function remains unclear due to its complex and heterogeneous symptoms. The present study aimed to use resting-state functional magnetic imaging data to explore effective connectivity between the right temporoparietal junction (RTPJ), one of the key brain regions associated with social impairment of individuals with ASD, and the whole brain to further deepen our understanding of the neuropathological mechanism of ASD. This study involved 1,454 participants from 23 sites from the Autism Brain Imaging Data Exchange (ABIDE) public dataset, which included 618 individuals with ASD and 836 with typical development (TD). First, a voxel-wise Granger causality analysis (GCA) was conducted with the RTPJ selected as the region of interest (ROI) to investigate the differences in effective connectivity between the ASD and TD groups in every site. Next, to obtain further accurate and representative results, an image-based meta-analysis was implemented to further analyze the GCA results of each site. Our results demonstrated abnormal causal connectivity between the RTPJ and the widely distributed brain regions and that the connectivity has been associated with social impairment in individuals with ASD. The current study could help to further elucidate the pathological mechanisms of ASD and provides a new perspective for future research.